Negative urgency combined with negative emotionality is linked to eating disorder psychopathology in community women with and without binge eating
Bibliographic record
Abstract
OBJECTIVE: Previous research has shown that negative emotionality (NE) and negative urgency (NU) are each risk factors for disordered eating behaviors among undergraduates and treatment-seekers. However, the interaction of these traits in community-based adults with clinical levels of binge eating is unknown and has implications for risk and maintenance models of disordered eating. METHOD: We examined a moderated-mediation model of cross-sectional associations among levels of NE (independent variable), NU (mediator), and eating disorder psychopathology (i.e., eating, shape, and weight concerns, and restraint; dependent variable) in 68 community-recruited women with current regular binge eating and 75 control women with no eating disorder history (group = moderator). Participants completed semi-structured diagnostic interviews and self-report questionnaires measuring NE, NU, eating disorder psychopathology, and anxiety and depression symptoms. RESULTS: After adjusting for anxiety and depression symptoms and body mass index, women with binge eating experienced greater NU and eating disorder psychopathology than control women with no eating disorder history. Despite similar levels of NE across groups, both groups exhibited an indirect effect of NE on eating disorder psychopathology via NU. DISCUSSION: Our findings suggest that greater NE, coupled with a propensity to engage in rash action when experiencing negative emotions, are associated with eating disorder psychopathology in women with and without eating disorders characterized by binge eating. These findings may help explain why some individuals engage in disordered eating behaviors when experiencing negative affect.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".